J. E. Medina Reyes

GODM: Graph Orthogonal Diffusion Models for Spatio-Temporal Forecasting

A novel framework (GODM) is proposed that adopts orthogonalization to decouple intricate temporal dynamics while employing spatial convolutions to simulate information flow across space and consistently outperforms state-of-the-art spatio-temporal diffusion models.